170 lines
6.7 KiB
Python
170 lines
6.7 KiB
Python
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import functions
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import config
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import imp
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while True:
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# ------------------------------------------- #
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# PART 1: Updating the notion trades database #
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# ------------------------------------------- #
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# Fetches the list of all trades stored in notion
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print("Fetching Data from Notion...", end=" ", flush=True)
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trades = functions.fetch_format_notion_trades(config.notion_db_id_trades)
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# Generates a list with unique tickers and no duplicates to reduce workload for the yfinance api
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print("Creating a list of unique tickers...", end=" ", flush=True)
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tickers = functions.filter_list_of_tickers(trades)
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# Configuration dependent execution:
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if config.calculate_benchmark == True:
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# Add the benchmark-ticker to the list of tickers to download data from yfinance from
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print("Adding benchmark-ticker...", end="", flush=True)
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tickers = functions.add_benchmark_ticker(tickers, config.ticker_benchmark)
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# Fetches & formats the complete history per ticker from yfinance
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print("Fetching & formating yfinance data", end="", flush=True)
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yf_data = functions.fetch_format_yf_data(tickers)
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# Calculates & stores a history per trade
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print("Calculating the history per trade...", end=" ", flush=True)
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history_per_trade = functions.calc_history_per_trade(trades, yf_data)
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# Configuration dependent execution:
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if config.update_notion == True:
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# Selects the most current values from the history per trade and overwrites them in the "trades" feteched from notion
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print("Selecting the most current values...", end=" ", flush=True)
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trades = functions.select_current_value_per_trade(trades, history_per_trade)
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# Updates the values in the notion database
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print("Updating the notion trades database", end="", flush=True)
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functions.push_notion_trades_update(trades)
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# ------------------------------------------------ #
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# PART 2: Updating the notion investments database #
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# ------------------------------------------------ #
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# Fetches the list of entries in the investment-overview database stored in notion
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print("Fetching & formating notion investments...", end=" ", flush=True)
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investments = functions.fetch_format_notion_investments(config.notion_db_id_investments)
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# Calculates & stores a history per ticker AND a total across all tickers indexed by the ticker name
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print("Calculating history per ticker...", end=" ", flush=True)
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history_per_ticker = functions.calc_history_per_ticker(history_per_trade, tickers, trades)
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# Configuration dependent execution:
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if config.update_notion == True:
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# Selects the most current values from the history per ticker and overwrites them in the "investments" feteched from notion
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print("Calculating current value per ticker...", end=" ", flush=True)
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investments = functions.select_current_value_per_ticker(investments, history_per_ticker)
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# Updates the values in the notion database
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print("Updating the notion ticker database", end="", flush=True)
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functions.push_notion_investment_update(investments)
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# ----------------------------------------- #
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# PART 3: Calculating Benchmark performance #
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# ----------------------------------------- #
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# Configuration dependent execution:
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if config.calculate_benchmark == True:
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# Creating benchmark trades
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print("Creating 'benchmark trades'...", end="", flush=True)
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benchmark_trades = functions.create_benchmark_trades(trades, yf_data)
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# Calculating benchmark trades
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print("Calculating the history per benchmark-trade...", end=" ", flush=True)
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history_per_benchmark_trade = functions.calc_history_per_trade(benchmark_trades, yf_data)
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# Calculates & stores a history for the benchmark
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print("Calculating benchmark-history overall...", end=" ", flush=True)
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history_benchmark = functions.calc_history_per_ticker(history_per_benchmark_trade, tickers, benchmark_trades)
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# Merging the benchmark_history into the ticker_history
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print("Merging the benchmark-history into the ticker-history...", end=" ", flush=True)
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history_per_ticker = functions.merge_histories(history_per_ticker, history_benchmark)
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# --------------------------------- #
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# PART 4: Updating the TRMNL Screen #
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# --------------------------------- #
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# Configuration dependent execution:
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if config.update_TRMNL == True:
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# Creates a list containing one date per week
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print("Creating a list with one entry per week...", end=" ", flush=True)
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list_filtered_dates = functions.create_list_filtered_dates(trades, config.trmnl_granularity)
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# Filter a weekly snapshot from the history per ticker
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print("Filtering the history per ticker to weekly values...", end=" ", flush=True)
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history_per_ticker_filtered = functions.filter_history_by_list(history_per_ticker, list_filtered_dates)
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# Prepare a new TRMNL update
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print("Constructing a TERMNL update object...", end=" ", flush=True)
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trmnl_update_object = functions.prep_trmnl_chart_udpate(
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history_per_ticker_filtered,
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series_to_show_1="total",
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data_to_show_1="current_value",
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series_to_show_2="benchmark",
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data_to_show_2="current_value"
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)
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# Push the update to TRMNL
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print("Updating a TERMNL screen...", end=" ", flush=True)
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functions.push_trmnl_update_chart(trmnl_update_object, config.trmnl_url_chart_1, config.trmnl_headers)
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# Prepare a new TRMNL update
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print("Constructing a TERMNL update object...", end=" ", flush=True)
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trmnl_update_object = functions.prep_trmnl_chart_udpate(
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history_per_ticker_filtered,
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series_to_show_1="total",
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data_to_show_1="current_irr",
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series_to_show_2="benchmark",
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data_to_show_2="current_irr"
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)
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# Push the update to TRMNL
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print("Updating a TERMNL screen...", end=" ", flush=True)
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functions.push_trmnl_update_chart(trmnl_update_object, config.trmnl_url_chart_2, config.trmnl_headers)
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# Prepare a new TRMNL update
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print("Constructing a TERMNL update object...", end=" ", flush=True)
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trmnl_update_object = functions.prep_trmnl_chart_udpate(
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history_per_ticker_filtered,
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series_to_show_1="total",
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data_to_show_1="total_performanance",
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series_to_show_2="benchmark",
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data_to_show_2="total_performanance"
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)
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# Push the update to TRMNL
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print("Updating a TERMNL screen...", end=" ", flush=True)
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functions.push_trmnl_update_chart(trmnl_update_object, config.trmnl_url_chart_3, config.trmnl_headers)
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# --------------------------- #
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# PART 5: Cool off and repeat #
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# --------------------------- #
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# Clear variables
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trades = {}
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yf_data = {}
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history_per_trade = {}
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tickers = []
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# Reload config
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imp.reload(config)
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# Logging
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print("Completed cycle at: {}".format(functions.datetime.datetime.now()))
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print("Waiting a few minutes before the next execution")
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print("---------------------------------------------------------------------------")
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# Wait for api-cooldown
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functions.time.sleep(config.programm_cooldown_time * 60) |